Machine learning non-isothermal study of the blade coating process (NIS-BCP) using non-Newtonian nanofluid with magnetohydrodynamic (MHD) and slip effects

The underlying investigation reports the effects of the magnetohydrodynamics (MHD) and non-linear slip coefficients on the coating thickness of the web/substrate during the blade coating process. Two dimensional analysis of the blade coating process is performed using non-Newtonian nanofluid model with the help of basic equations of fluid dynamics are performed. Firstly, the system of equations of motion (EOM) is transformed into the non-dimensional form by using the scaling factors. Secondly, the modeled equations are further simplified with the help of lubrication approximation theory (LAT). The resulting boundary value problem is transformed into stream function to eliminate the pressure gradient from the flow equation and then numerically tackled with the Matlab built-in function bvp4c with the method of false position (Regula-Falsi Method). A comparative study of numerical data with results simulated by artificial neural networks (ANN) found that results are in excellent agreement. The impact of sundry parameters on physical quantities is examined through graphical representation. Results indicate that the influence of magnetohydrodynamics (MHD), nanoparticle and slip effects cannot be ignored during the blade coating flow, as a significant impact of these parameters is observed on velocity, temperature, pressure, coating thickness, blade load, and streamlines.